Illumination and resolution analyses on marine seismic data acquisitions by the adjoint wavefield method

Kun Sung Li, How Wei Chen

Research output: Contribution to journalArticlepeer-review


We applied a wave-equation based adjoint wavefield method for seismic illumination and resolution analyses. A two-way wave-equation is used to calculate directional and diffracted energy fluxes for waves propagating between sources and receivers to the subsurface target. The first-order staggered-grid pressure-velocity formulation, which lacks the characteristic of being self-adjoint is further validated and corrected to render the modeling operator before its practical application. Despite most published papers on synthetic kernel research, realistic applications to two field experiments are demonstrated and emphasize its practical needs. The Fréchet sensitivity kernels are used to quantify the target illumination conditions. For realistic illumination measurements and resolution analyses, two completely different survey geometries and nontrivial pre-conditioning strategies based on seismic data type are demonstrated and compared. From illumination studies, particle velocity responses are more sensitive to lateral velocity variations than pressure records. For waveform inversion, the more accurately estimated velocity model obtained the deeper the depth of investigation would be reached. To achieve better resolution and illumination, closely spaced OBS receiver interval is preferred. Full waveform approach potentially provides better depth resolution than ray approach. The quantitative analyses, a by-product of full waveform inversion, are useful for quantifying seismic processing and depth migration strategies.

Original languageEnglish
Pages (from-to)621-632
Number of pages12
JournalTerrestrial, Atmospheric and Oceanic Sciences
Issue number6
StatePublished - Dec 2012


  • Adjoint method
  • Illumination analysis
  • Pressure-velocity wave equation
  • Reciprocity
  • Resolution analysis
  • Self-adjoint operator
  • Sensitivity kernels


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